Adaptive clustering for segmentation of multi-sensor images

Sunanda Mitra, Molly Dickens, Surya Pemmaraju

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Automatic detection or recognition of specific objects from a sequence of images acquired under varying conditions and from different modalities requires careful segmentation. We present here the use of an adaptive neuro-fuzzy clustering technique for image segmentation and boundary detection for better extraction of the dominant features in images of the same scene acquired by synthetic aperture radar (SAR) and electro-optic (EO) sensors. The advantage of such adaptive segmentation is clearer identification of objects that appear differently due to different sensor characteristics.

Original languageEnglish
Title of host publication1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1649-1651
Number of pages3
ISBN (Print)078034863X, 9780780348639
DOIs
StatePublished - 1998
Event1998 IEEE International Conference on Fuzzy Systems, FUZZY 1998 - Anchorage, United States
Duration: May 4 1998May 9 1998

Publication series

Name1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence
Volume2

Conference

Conference1998 IEEE International Conference on Fuzzy Systems, FUZZY 1998
CountryUnited States
CityAnchorage
Period05/4/9805/9/98

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    Mitra, S., Dickens, M., & Pemmaraju, S. (1998). Adaptive clustering for segmentation of multi-sensor images. In 1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence (pp. 1649-1651). [686367] (1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZY.1998.686367